Superconducting processor micro-architecture construction method based on riscv

Abstract

The invention discloses a superconductive processor micro-architecture construction method based on RISC-V. The superconductive processor micro-architecture construction method aims at achieving efficient operation and performance optimization of a processor in an ultralow-temperature environment. The method comprises the following steps: firstly, designing a functional module and an assembly line of a processor based on an RISC-V instruction set, and presetting initial parameters; next, micro-architecture parameters are selected and optimized through a simulation tool and a multi-objective optimization algorithm, and balance among performance, power consumption and chip area is ensured; then, a low-temperature cooling system is designed and integrated, and it is ensured that the processor stably operates in an ultralow-temperature environment of 2-4 Kelvin; the function correctness and the performance efficiency of the processor are verified through simulation and actual testing; and finally, manufacturing a key assembly by using a superconducting material, and integrally packaging the processor and the cooling system. By combining refined performance optimization and a comprehensive performance evaluation algorithm, the performance and energy efficiency of the processor in a complex environment can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer processor design, and in particular to a method for constructing a superconducting processor micro-architecture based on RISCv. Background Art

[0002] As processor performance continues to improve, the power consumption and heat generation bottlenecks faced by traditional semiconductor technology have become increasingly prominent. In order to break through this bottleneck, superconducting technology has gradually become a key direction for high-performance computing due to its low power consumption and zero resistance loss. At the same time, RISC-V, as an open and modular instruction set architecture, has the characteristics of high flexibility and good scalability, and has been widely used in customized processor design.

[0003] However, there are still many technical difficulties in the construction of superconducting processor microarchitecture for RISC-V architecture in the existing technology, especially in terms of how to design a microarchitecture suitable for superconducting environment, how to run the processor efficiently in low temperature environment, how to optimize the balance between power consumption and performance, etc. There is a lack of effective methodology and solutions. In order to solve the above technical difficulties, a construction method for superconducting processors is needed, which can not only run stably at extremely low temperatures, but also improve its overall performance and energy efficiency through simulation optimization. Summary of the invention

[0004] The purpose of the present invention is to provide a method for constructing a superconducting processor microarchitecture based on the RISC-V architecture. The method has the advantages of high efficiency, low power consumption, flexibility and scalability, and is intended to solve the problems of complex processor design, difficult power consumption control, and insufficient parameter optimization in a superconducting environment.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for constructing a superconducting processor microarchitecture based on RISCv, comprising the following steps:

[0006] S1. Micro-architecture design: Based on the RISC-V instruction set architecture, design the functional modules and pipelines of the processor, and preset preliminary parameters to provide input basis for subsequent calibration and optimization; S2. Parameter selection and simulation optimization: select and optimize micro-architecture parameters through simulation tools and optimization algorithms to ensure the balance of performance, power consumption and area; S3. Integration of low-temperature cooling system: design and integrate a cooling system that adapts to the superconducting environment to ensure stable operation of the processor under ultra-low temperature conditions; S4. Functional verification and performance testing: verify the correctness of the processor function through simulation and actual testing, evaluate performance and optimize; S5. Manufacturing and packaging: use superconducting materials to manufacture key components, and integrate the processor and cooling system into a package.

[0007] Preferably, the micro-architecture design includes the following steps: a. Based on the RISC-V instruction set architecture, design the functional modules of the processor, the functional modules including the instruction pipeline, execution unit, register file, memory management unit and input / output interface; b. Expand the RISC-V instruction set, add new instructions for superconducting processors, including quantum bit initialization instructions, quantum gate operation instructions and superconducting state detection instructions, and adjust the instruction decoding logic to make the new instructions compatible with the existing instruction set; c. Design at least three pipelines, and integrate out-of-order execution and instruction-level parallel execution mechanisms in each pipeline; d. Preset micro-architecture parameters to provide input basis for the micro-architecture preliminary parameter calibration algorithm in subsequent steps.

[0008] Preferably, the parameter selection and simulation optimization include the following steps: a. According to the characteristics of the low-temperature superconducting environment, determine the number of execution units, cache levels and capacity, and the size of the register group, and limit the specific range of each parameter to adapt to the balance requirements of performance, power consumption and area; b. Use simulation analysis tools to perform performance simulation on the selected microarchitecture parameters, and the simulation results include the number of instructions executed per second, power consumption and chip area; c. Use a multi-objective optimization algorithm to adjust the microarchitecture parameter combination based on the simulation results to achieve a balance between performance, power consumption and chip area; d. Apply a microarchitecture preliminary parameter calibration algorithm to calibrate the initially set parameters, use a refined performance optimization algorithm to further optimize, and determine the final optimized configuration through comprehensive performance evaluation and decision-making algorithms.

[0009] Preferably, the integration of the cryogenic cooling system includes the following steps: a. designing a cryogenic cooling system for a superconducting processor, the cooling system should be able to maintain the operating temperature of the processor between 2 Kelvin and 4 Kelvin; b. integrating the cooling system into the packaging structure of the processor and tightly connecting it to the core structure of the processor, with the total length of the cooling path not exceeding 10 mm; c. the cooling system adopts liquid helium or dilution refrigeration technology.

[0010] Preferably, the functional verification and performance testing include the following steps: a. performing functional verification on a simulation platform for different workloads to ensure that all instructions can be executed correctly; b. testing the number of instructions executed per second, average energy consumption and delay time performance indicators, and performing statistical analysis on the test results; c. based on the results of the performance test, identifying performance limiting factors through bottleneck analysis, and introducing optimization measures in the micro-architecture.

[0011] Preferably, the manufacturing and packaging include the following steps: a. using superconducting materials to manufacture key components of the processor, the thickness of the material ranges from 5 nanometers to 100 nanometers; b. making a superconducting Josephson junction with a size not exceeding 500 nanometers to ensure that the logic circuit of the processor has superconducting properties; c. packaging the processor chip together with the low-temperature cooling system, and the overall size after packaging does not exceed 50 mm×50 mm×10 mm.

[0012] Preferably, the micro-architecture preliminary parameter calibration algorithm comprises the following steps: a. collecting initial micro-architecture parameter data X = {x1, x2, ..., x n} and environmental parameters E={e1,e2,...,e m}, the microarchitecture parameters include execution unit configuration, pipeline depth and cache size, and the environmental parameters include cooling system efficiency and temperature; b. Calculate the preliminary performance estimate P estimate , where ω i and e j is the weight coefficient, reflecting the impact of each parameter on the performance; c. According to the performance error ΔP = P target -P estimate , perform preliminary calibration on the microarchitecture parameters, the correction amount is: Δx i =α·ΔP, where α is the calibration coefficient; d. Update the microarchitecture parameters to obtain the calibrated parameters X′={x1′,x′2,...,x′ n}.

[0013] Preferably, the refined performance optimization algorithm comprises the following steps: a. receiving the calibration parameter X′ and the error evaluation result output by the micro-architecture preliminary parameter calibration algorithm, and the external condition O={o1, o2, ..., o n}, the external conditions include cooling system performance and ambient temperature; b. Based on the error propagation model, the error is corrected, and the correction function f is defined as: f(Δx i ,o i )=γ·Δx i +δ·h(o i ), where γ is the error adjustment coefficient, h(o i ) is a nonlinear function related to external conditions; c. Update the microarchitecture parameters according to the corrected error propagation results: x″=x i ′+f(Δx i ,o i ), and obtain the modified parameter set X″={x1″,x′2′,...,x′ n ′}.

[0014] Preferably, the comprehensive performance evaluation and decision algorithm comprises the following steps: a. receiving the output results of the micro-architecture preliminary parameter calibration and refined performance optimization, including the calibrated parameters X′, the optimized parameters X″ and the accurate performance prediction P accurate ; b. Use the nonlinear combination function g to perform a comprehensive performance evaluation on the above results. The nonlinear combination function is defined as: Among them, β1 and β2 are dynamic weights, which are adaptively adjusted according to different conditions; c. According to the comprehensive performance evaluation results, the dynamic weight adjustment mechanism is applied; d. The final comprehensive performance index S and the optimized microarchitecture configuration are output.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] 1. The present invention sets a dedicated micro-architecture design scheme based on the RISC-V instruction set architecture and combines the micro-architecture preliminary parameter calibration algorithm to enable the processor to run efficiently in a superconducting environment, thereby achieving the effect of improving processor performance and reducing power consumption. Compared with traditional processor designs, the present invention can dynamically adjust micro-architecture parameters to adapt to ultra-low temperature environments, and achieve higher instruction execution efficiency through algorithm optimization.

[0017] 2. By integrating a cryogenic cooling system, the present invention achieves stable operation in an ultra-low temperature environment of 2 to 4 Kelvin. The use of liquid helium or dilution refrigeration technology, combined with a tight cooling path design, significantly improves the cooling efficiency, achieving the advantages of reducing processor power consumption and improving its long-term stability.

[0018] 3. The multi-objective optimization algorithm and the refined performance optimization algorithm are adopted. Through simulation and analysis of the performance of the processor under different loads, the micro-architecture parameter combination is dynamically optimized, so that the best balance between performance, power consumption and chip area is achieved. Compared with the existing fixed parameter design method, the present invention can adjust parameters more flexibly during the design and optimization process, thereby improving the overall performance of the processor.

[0019] 4. The RISC-V instruction set has been expanded. The present invention has added quantum bit control instructions and superconducting logic operation instructions specifically for superconducting processors, achieving the effect of enhancing the flexibility and expansion capabilities of the processor. This design enables the processor to support more complex operations, suitable for quantum computing and other superconducting logic operation scenarios, and provides a wider application space for future processor customization and high-performance computing. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a flow chart of the main steps of the method for constructing a superconducting processor micro-architecture based on RISC-V of the present invention;

[0021] Figure 2A schematic diagram of the micro-architecture design steps of the present invention;

[0022] Figure 3 Schematic diagram of parameter selection and simulation optimization steps of the present invention;

[0023] Figure 4 It is a schematic diagram of the integration steps of the low temperature cooling system of the present invention;

[0024] Figure 5 This is a schematic diagram of the functional verification and performance testing steps of the present invention;

[0025] Figure 6 A schematic diagram of the manufacturing and packaging steps of the present invention;

[0026] Figure 7 A schematic diagram of the steps of the micro-architecture preliminary parameter calibration algorithm of the present invention;

[0027] Figure 8 Schematic diagram of the steps of the refined performance optimization algorithm of the present invention. DETAILED DESCRIPTION

[0028] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] See also Figures 1 to 8 The present invention provides a method for constructing a superconducting processor micro-architecture based on RISC-V. By expanding the RISC-V instruction set and combining the characteristics of the superconducting processor, a processor design method suitable for quantum computing and traditional computing tasks is formed. This method not only has the flexibility and modular design of the traditional RISC-V architecture, but also optimizes the specific needs of the superconducting processor, aiming to provide efficient computing power and a low-energy working environment. The construction method specifically includes the following steps:

[0030] S1 micro-architecture design: The core of this step is to design the functional modules and pipeline structure of the processor based on the RISC-V instruction set architecture, and lay the foundation for subsequent calibration and optimization.

[0031] Functional module design: In the initial stage of microarchitecture design, it is first necessary to design the core functional modules of the processor based on the RISC-V instruction set. These modules include but are not limited to: Instruction pipeline: The multi-level instruction pipeline of the processor helps to improve the execution efficiency of instructions and allows multiple instructions to be in different execution stages at the same time. Execution unit: Responsible for executing various instructions from the instruction pipeline, which may include integer and floating-point execution units. Register file: Used to temporarily store data and instructions generated during processing so that the processor can quickly access key data. Memory management unit (MMU): Responsible for managing read and write access to memory and interaction with external memory. Input / output interface: Provides the processor with the ability to communicate with external devices and supports data input and output. RISC-V instruction set extension: In order to meet the needs of superconducting processors for quantum computing, the present invention has been expanded on the basis of the RISC-V instruction set, adding three types of instructions related to quantum computing:

[0032] Quantum bit initialization instruction: This instruction is used to initialize the superconducting quantum bit and set its state to an executable basic state.

[0033] Quantum gate operation instruction: This instruction is used to perform common quantum operations, such as quantum gate logic operations, including Hadamard gate, CNOT gate, etc.

[0034] Superconducting state detection instruction: This instruction allows the processor to detect the state of the superconducting device to ensure the stability and correctness of the quantum bit.

[0035] These new instructions need to be compatible with RISC-V's existing instruction set, so the instruction decoding logic needs to be adjusted so that the processor can process both traditional instructions and quantum instructions at the same time, ensuring efficient performance and flexibility of the instruction set.

[0036] Three-stage pipeline design In order to maximize the instruction execution efficiency of the processor, the present invention designs at least a three-stage instruction pipeline structure. In this structure, each stage of the pipeline supports out-of-order execution and instruction level parallel execution (ILP) mechanism.

[0037] Out-of-order execution: Allows the processor to adjust the execution order of instructions based on data dependencies, improving the utilization of the execution units.

[0038] Instruction-level parallelism (ILP): By executing multiple instructions in parallel, the overall throughput is improved, especially when processing concurrent computing tasks, which can significantly improve performance.

[0039] Preset Microarchitecture Parameters After the microarchitecture design is completed, preliminary parameters need to be set for each module and pipeline. These parameters include instruction cache size, pipeline depth, number of execution units, etc. These preset parameters will be used as input for parameter optimization and calibration in subsequent steps.

[0040] The working principle of the present invention is to build a highly modular and scalable processor architecture, so that it can not only perform traditional computing tasks, but also support quantum computing tasks based on superconducting technology. By extending the RISC-V instruction set, the processor can easily handle tasks such as initialization, operation and detection of quantum bits. At the same time, the three-level pipeline structure is adopted and combined with out-of-order execution and instruction-level parallelism to maximize the execution efficiency of the processor.

[0041] S2, parameter selection and simulation optimization, select and optimize micro-architecture parameters through simulation tools and optimization algorithms to ensure the balance of performance, power consumption and area; the parameter selection and simulation optimization step of the present invention aims to select and adjust the micro-architecture parameters of the processor through tool simulation and optimization algorithms to ensure that the processor achieves an ideal balance between performance, power consumption and chip area. Through a series of precise calculations and simulations, this step can ensure that the designed processor works efficiently in a superconducting environment and meets the strict requirements of power consumption, performance and area.

[0042] a. Determination of the number of execution units, cache levels and capacity, and register group size: In a low-temperature superconducting environment, the operating conditions of the processor are different from those of a traditional silicon-based chip environment. In order to fully utilize the advantages of superconducting materials and adapt to this environment, the present invention is optimized based on the following core parameters:

[0043] Number of execution units: The number of execution units is determined according to the target task type and workload of the processor. For high-concurrency computing tasks, increasing the number of execution units helps to improve throughput, but it will increase power consumption and chip area, so it is necessary to strike a balance between performance improvement and increased power consumption. Cache hierarchy and capacity: The design of cache hierarchy and capacity is crucial to the overall performance of the processor. Taking into account the characteristics of superconducting processors in low-temperature environments, the present invention determines the appropriate cache hierarchy (such as L1, L2 cache) and the capacity of each cache layer through simulation analysis. The selection of cache capacity requires a balance between speeding up data access speed and controlling power consumption and area. Size of register group: Registers are important components in the processor for storing temporary data, and their size determines whether the processor can quickly access frequently used data. The present invention determines the size of the register group according to the workload requirements, and ensures that while increasing the number of registers to improve performance, it does not lead to excessive increases in power consumption and chip area. By quantifying and setting these core parameters, the present invention ensures the best performance and power consumption balance in a low-temperature superconducting environment.

[0044] b. Performance simulation of micro-architecture parameters: After determining the preliminary parameters, use performance simulation tools to evaluate these parameters. The present invention simulates different combinations of micro-architecture parameters through simulation tools (such as Gem5, Simulators, etc.), and the simulation output results include the following indicators:

[0045] Instructions per second (IPC): used to measure the computing efficiency of the processor. Power consumption: measures the energy consumption level of the processor under different loads to ensure that it meets the low energy consumption requirements in the superconducting environment. Chip area: determines whether the overall area of ​​the processor is reasonable by evaluating the layout and resource usage of each module. These simulation data provide important input basis for subsequent multi-objective optimization.

[0046] c. Application of multi-objective optimization algorithm: The present invention uses a multi-objective optimization algorithm to comprehensively balance and optimize the performance, power consumption and chip area of ​​the processor. The optimization algorithm automatically adjusts the micro-architecture parameter combination based on the simulation results to achieve the best balance between multiple objectives. Specifically, the optimization algorithm evaluates and weighs the relationship between the following three:

[0047] Performance: Increase the number of instructions executed per second by adjusting the number of execution units and pipeline depth. Power consumption: Reduce overall energy consumption by limiting cache capacity and optimizing register group size. Chip area: Reduce the physical area of ​​the processor by controlling the size of each module. The algorithm runs in an iterative manner, and re-simulates and evaluates after each parameter adjustment until the optimal parameter combination that takes into account performance, power consumption and area is found. Among them, the multi-objective optimization algorithm of the present invention aims to achieve the best balance between multiple optimization goals such as performance, power consumption and chip area. The algorithm combines the simulation results and finds the optimal solution by gradually adjusting the micro-architecture parameter combination. It is characterized by comprising the following steps:

[0048] C1. Define the initial micro-architecture parameter combination: Set the initial micro-architecture parameter vector X = {x1, x2, ..., x n} and optimization target vector G = {g1,g2,g3} where g1 represents performance (number of instructions executed per second), g2 represents power consumption, and g3 represents chip area. The goal is to achieve G by optimizing X;

[0049] C2. Objective function construction: Construct an objective function for each optimization target as follows:

[0050] The performance objective function f1(X) represents the number of instructions executed per second; the power consumption objective function f2(X) represents the energy consumption; the area objective function f3(X) represents the chip area. The above objective functions can be calculated through the results of simulation tools.

[0051] C3. Multi-objective optimization strategy: Use a multi-objective optimization algorithm to balance different objectives and generate new parameter combinations. The objective function values ​​of each iteratively generated parameter combination X′ are f1(X′), f2(X′), f3(X′), and are evaluated according to the preset objective weights:

[0052] G total =ω1·f1(X′)+ω2·f2(X′)+ω3·f3(X′), where ω1, ω2 and ω3 are the weight coefficients of each target respectively.

[0053] C4. Iterative optimization: According to the evaluation results, gradually adjust the parameter combination to generate a new round of optimization solutions until the optimization stop condition is reached (such as the upper limit of the number of iterations or the convergence of the optimization results). During each iteration, the objective function value gradually approaches the optimal solution;

[0054] C5. Output the optimal parameter combination

[0055] Finally, the optimal microarchitecture parameter combination X is output * ={x*1,x*2,...,x* n} and generates final performance, power, and area estimates based on the optimization results.

[0056] d. Calibration and optimization of micro-architecture preliminary parameters: After the preliminary optimization is completed, the present invention applies a micro-architecture preliminary parameter calibration algorithm to further refine the preliminary set parameters. The calibration algorithm is performed by the following steps:

[0057] Fine-tune initial parameters: Based on the simulation and optimization results, fine-tune the initial parameter settings of the execution unit, cache, and register group to ensure that the performance and power consumption of each module meet the expected requirements. Performance optimization algorithm: Based on the preliminary calibration, use a refined performance optimization algorithm to deeply optimize the key performance indicators of the processor (such as the number of instructions executed per second, power consumption, etc.). This step of optimization can ensure that the processor performs well under different task loads and can run efficiently. Comprehensive performance evaluation and decision-making: Finally, the present invention selects the most suitable parameter combination through a comprehensive performance evaluation and decision-making algorithm, combined with performance simulation data and optimization algorithm output. This process ensures the stability and efficiency of the processor in a superconducting environment, while taking into account power consumption and area limitations. Through the optimization and simulation of micro-architecture parameters, the present invention can achieve the best balance between performance, power consumption and chip area. The core idea of ​​parameter selection and optimization is: through simulation analysis and algorithm iteration, continuously adjust and evaluate the design of the processor to ensure that it can run stably and efficiently in a low-temperature superconducting environment.

[0058] S3. Integration of low-temperature cooling system: Design and integrate a cooling system adapted to superconducting environment to ensure stable operation of the processor under ultra-low temperature conditions; In order to ensure that the superconducting processor based on RISC-V can operate stably under extremely low temperature conditions, the present invention designs and integrates a low-temperature cooling system suitable for superconducting environment. The cooling system can ensure that the processor can continue to operate in the ultra-low temperature range of 2 Kelvin to 4 Kelvin, and at the same time has a compact structural design, which ensures cooling efficiency while reducing the packaging volume and the length of the cooling path.

[0059] a. Design of low-temperature cooling system: Superconducting processors rely on extremely low temperature conditions to maintain the superconducting state. Therefore, the design of the cooling system is crucial to the normal operation of the processor. The present invention designs a cooling system that can maintain the operating temperature of the processor between 2 Kelvin and 4 Kelvin, ensuring that the core components of the processor operate efficiently in the superconducting state. Determination of ultra-low temperature range: In order for superconducting materials to exhibit zero resistance characteristics, the processor must operate in an extremely low temperature environment. The cooling system of the present invention controls the operating temperature of the processor between 2 Kelvin and 4 Kelvin by adopting efficient refrigeration technology. This temperature range is sufficient to maintain the superconducting state and ensure that the processor can continue to operate efficiently. Selection of cooling medium: In order to achieve the required ultra-low temperature, the present invention uses liquid helium or dilution refrigeration technology. These two technologies can effectively reach and maintain low temperatures close to absolute zero, ensuring that the temperature of the processor remains stable during long-term operation.

[0060] b. Integration of cooling system and processor: The cooling system not only needs to have efficient cooling capacity, but also must be closely integrated with the packaging structure of the processor to minimize the length of the cooling path, ensure that the heat can be quickly taken away, and prevent the processor from overheating. The present invention proposes a compact cooling path design, which reduces heat loss in the cooling path by integrating the cooling system into the packaging structure of the processor and directly connecting it to the core components. Limitation of cooling path length: In order to improve cooling efficiency, the cooling path length designed by the present invention does not exceed 10 mm. Such a short cooling path ensures that the cooling medium can quickly and effectively conduct heat and ensure the stability of the core temperature of the processor. In addition, the shorter cooling path also reduces the volume of the packaging structure, which is conducive to the miniaturization and high-density integration of the entire system. Integrated design of the packaging structure: The cooling system and the processor are packaged in an integral structure, and the cooling medium is connected to the heat source of the processor by direct contact. This design can not only reduce heat transfer losses, but also ensure that the cooling system provides sufficient cooling effect without increasing the complexity of the processor packaging.

[0061] c. Application of liquid helium or dilution refrigeration technology: In order to achieve an ultra-low temperature working environment, the present invention adopts liquid helium and dilution refrigeration technology as the core cooling solution: Liquid helium cooling: Liquid helium is currently the most commonly used low-temperature cooling medium, which can easily reach a temperature range of 2-4 Kelvin. The liquid helium cooling system absorbs and takes away the heat generated by the processor by circulating liquid helium, keeping it at the low temperature required for the superconducting state. Dilution refrigeration technology: Dilution refrigeration is a low-temperature refrigeration technology based on the dilution effect of a mixed gas of helium-3 and helium-4 isotopes, which can further reduce the temperature to near absolute zero. Dilution refrigeration technology is often used in situations where more stable ultra-low temperatures are required, and is suitable for keeping the processor running within the optimal temperature range for a long time. The combination or use of these two technologies alone provides a stable and reliable cooling environment for the processor, ensuring that the temperature fluctuations of the processor are controlled within an acceptable range during long-term operation.

[0062] The cooling system of the present invention can effectively control the core temperature of the processor by tightly integrating the cooling medium (such as liquid helium or dilution refrigeration) into the package of the processor. The cooling system reduces the delay of heat conduction by optimizing the cooling path length, so that the heat of the processor during operation can be quickly transferred to the cooling medium, ensuring that the processor is continuously maintained at an ultra-low temperature of 2-4 Kelvin. This not only maintains the zero resistance characteristics of the superconducting material, but also prolongs the working life of the processor.

[0063] S4, functional verification and performance testing, verify the correctness of processor functions through simulation and actual testing, evaluate performance and optimize; after the processor design is completed, functional verification and performance testing are key steps to ensure its design correctness and operating efficiency. The present invention verifies the functional correctness of the processor through simulation and actual testing, and evaluates its performance under different workloads. Through these tests, the performance bottlenecks in the micro-architecture are identified and optimized, and the overall performance of the processor is further improved.

[0064] a. Functional verification on the simulation platform: In order to ensure that each instruction module of the processor can be executed correctly, the present invention performs functional verification on the simulation platform for different workloads. The purpose of this step is to ensure that all extended RISC-V instructions and instructions related to quantum computing can be correctly executed according to the design requirements, and the processor can remain stable in different computing scenarios. Selection of simulation platform: The present invention uses dedicated simulation tools (such as Gem5, QEMU, etc.) to build a simulation environment. In this environment, the microarchitecture and instruction set of the processor can be fully simulated to test whether its functions meet the design expectations. Verification of different workloads: In order to fully verify the functions of the processor, the present invention designs multiple workload test scenarios, including but not limited to integer calculations, floating-point calculations, memory access and quantum computing tasks. Through these diverse workload tests, it is ensured that the processor can correctly execute all instructions in various tasks, including traditional RISC-V instructions and newly added superconducting quantum computing instructions. Instruction correctness verification: During the simulation process, the execution of all instructions is recorded to ensure that the entire process from instruction fetch to final execution of each instruction meets the design requirements. If it is found that some instructions are executed incorrectly during the simulation process, the system will automatically mark and return error information for subsequent adjustments.

[0065] b. Performance testing and statistical analysis: After the functional verification is completed, the present invention conducts detailed tests on the key performance indicators of the processor. These performance tests not only help to evaluate the working performance of the processor under different loads, but also provide data support for subsequent performance optimization. Number of instructions executed per second (IPC): IPC is one of the core indicators for measuring processor efficiency. The present invention records the number of instructions executed by the processor per second by running multiple different workloads on the simulation platform. A high IPC value indicates that the processor can efficiently process instructions in parallel, while a low IPC value may indicate the existence of a performance bottleneck. Average energy consumption test: The energy consumption of the processor is a key design factor, especially in a superconducting processor environment, where low energy consumption is essential for maintaining a low temperature state. The present invention tests the energy consumption performance of the processor under different loads, calculates its average energy consumption value of executing instructions per second, and analyzes the relationship between energy consumption and performance. Delay time test: Delay time is a key indicator for the processor to respond to and execute tasks. The present invention analyzes the part of the microarchitecture that may cause delays by recording the execution delays of different instructions. Higher delays may indicate that the processor has bottlenecks or design defects in certain modules. Statistical analysis: After the test is completed, the present invention conducts statistical analysis on the above performance indicators. By summarizing and comparing the performance data under different workloads, the overall performance of the processor is analyzed. This analysis process provides detailed data support for subsequent performance optimization.

[0066] c. Performance bottleneck analysis and micro-architecture optimization: Based on performance testing and data analysis, the present invention further identifies performance limiting factors through bottleneck analysis, and takes corresponding optimization measures to improve the overall efficiency of the processor. Bottleneck analysis: Through the data of performance testing, the present invention uses bottleneck analysis tools to identify the limiting factors of processor performance. For example, during the execution of instructions, if it is found that the utilization rate of a certain level of pipeline or execution unit is too low or the waiting time is too long, it may indicate that the module is a performance bottleneck. Bottleneck analysis mainly focuses on the following aspects: Pipeline blocking: If some instructions wait too long in the pipeline, it may indicate that the design of the pipeline needs to be optimized. Cache miss: If it is found that the cache hit rate of the memory management unit is low, it may be necessary to adjust the cache hierarchy or capacity. Execution unit utilization: Low execution unit utilization may indicate that there are problems with instruction scheduling or parallelization design. Micro-architecture optimization measures: Based on the results of bottleneck analysis, the present invention adjusts and optimizes the micro-architecture to eliminate performance bottlenecks.

[0067] Specific optimization measures include: Pipeline depth optimization: adjust the pipeline depth and the parallelism of the execution unit to improve the execution efficiency of the pipeline. Cache design adjustment: according to the test results, appropriately increase the cache capacity or optimize the cache hierarchy to improve the cache hit rate. Instruction scheduling optimization: by optimizing the instruction scheduling algorithm, ensure that the processor can maximize the use of the parallelism of the execution unit, thereby improving the overall throughput. Through these optimization measures, the overall performance of the processor has been significantly improved, ensuring its efficiency in actual operation.

[0068] The functional verification and performance testing steps of the present invention ensure that all instructions can be correctly executed by performing comprehensive functional verification on the simulation platform, and further optimize the micro-architecture design through detailed performance testing and bottleneck analysis. The simulation platform provides an efficient verification environment, while performance testing and statistical analysis provide a scientific basis for the continuous optimization of the processor.

[0069] S5, manufacturing and packaging, using superconducting materials to manufacture key components, and integrating and packaging the processor with the cooling system. The manufacturing and packaging steps of the present invention are intended to use superconducting materials to manufacture key components of the processor, and tightly integrate and package the processor with the cryogenic cooling system. This step not only ensures that the processor has superconducting properties, but also ensures the stability and efficiency of the processor under ultra-low temperature conditions through precision manufacturing and compact packaging.

[0070] a. Superconducting material manufacturing of key components: In order to ensure that the processor can exhibit superconducting properties in a low-temperature environment, the present invention uses high-performance superconducting materials to manufacture key components of the processor. Superconducting materials can exhibit zero resistance characteristics in an extremely low-temperature environment, thereby significantly reducing power consumption and improving processor performance.

[0071] Selection and application of superconducting materials: The present invention uses superconducting materials with a thickness ranging from 5 nanometers to 100 nanometers for manufacturing. Superconducting materials generally include niobium (Nb), lead (Pb) or oxide high-temperature superconductors, etc. These materials can maintain zero resistance characteristics in an environment close to absolute zero. By using thin film manufacturing technology, these materials can be precisely deposited on key components of the processor to ensure their high efficiency in ultra-low temperature environments. Material thickness control: In order to ensure the superconducting effect, the present invention strictly controls the thickness of the superconducting material between 5 nanometers and 100 nanometers. This thickness range can provide sufficient mechanical strength and conductivity while maintaining superconducting properties. Precise control of thickness is achieved through deposition techniques such as molecular beam epitaxy or chemical vapor deposition.

[0072] b. Fabrication of superconducting Josephson junction: Josephson junction is the core component of the logic circuit of superconducting processor, which can realize logical operation in superconducting state by using quantum effect. The present invention ensures that the logic circuit of the processor has superconducting characteristics and can operate efficiently in ultra-low temperature environment by fabricating superconducting Josephson junction with a size not exceeding 500 nanometers. Function of Josephson junction: Josephson junction is a structure formed by sandwiching a thin insulating layer between two superconducting materials, which can realize the coherent flow of superconducting electrons through quantum tunneling effect. It plays a vital role in the logic circuit of the processor, and can complete switching operations under ultra-low temperature conditions without generating resistance. In order to ensure the superconducting characteristics of Josephson junction, the present invention adopts high-precision nano-manufacturing technology to control the size of Josephson junction within 500 nanometers. This tiny size can not only increase the operating speed of the processor, but also reduce the power consumption of the circuit. Nano-scale manufacturing technology ensures the high-density integration of Josephson junction in the processor, so that the processor has excellent logic processing capabilities.

[0073] c. Packaging of processor and cooling system: The present invention integrates and packages the processor chip with the low-temperature cooling system to form a compact overall structure. This packaging design not only takes into account the cooling efficiency, but also takes into account the volume requirements of the processor, ensuring that the packaged processor can operate efficiently in an extremely low temperature environment. Package size control: The present invention integrates and packages the processor chip with the cooling system, and the overall size after packaging does not exceed 50 mm × 50 mm × 10 mm. This compact size design helps to reduce the length of the cooling path, thereby improving the cooling efficiency, while also ensuring that the volume of the entire processor system is suitable for various application scenarios, including quantum computing and high-performance computing. Packaging process: In order to ensure the effective integration of the processor and the cooling system, the present invention adopts advanced packaging technology. During the packaging process, the processor chip and the cooling system are connected by a high thermal conductivity material to ensure that the heat generated by the processor can be quickly transferred to the cooling system and keep the temperature of the processor core within the range of 2 Kelvin to 4 Kelvin. In addition, the packaging material also needs to have an extremely low thermal expansion coefficient to adapt to temperature changes in an ultra-low temperature environment. The manufacturing and packaging steps of the present invention manufacture the key components of the processor by using superconducting materials, and integrate the processor and the cooling system in a compact packaging structure. By using thin film deposition technology and nanoscale Josephson junction manufacturing, the processor can maintain its superconducting properties in ultra-low temperature environments. The packaged processor is not only small in size and high in efficiency, but also able to operate stably under low temperature conditions.

[0074] The preliminary parameter calibration algorithm of the present invention is a systematic method for adjusting the initial parameters of the processor microarchitecture to ensure that the processor performance, power consumption and other targets can meet the requirements under specific workload and environmental conditions. The algorithm not only takes into account the parameters of the microarchitecture itself, but also takes into account external environmental parameters such as the cooling system.

[0075] a. Parameter source and initial setting: Before starting calibration, it is necessary to collect the initial parameters of the microarchitecture and the environment parameters. The sources of these parameters include: microarchitecture parameter vector X = {x1, x2, ..., x n}: These parameters include the configuration of the execution unit, the depth of the pipeline, the cache size, etc. These parameters can be obtained from the design specifications and initial design of the processor, and are the choices of designers in the early stages of processor architecture design. Environmental parameters E = {e1, e2, ..., e m Environmental parameters include cooling system efficiency, coolant flow rate, temperature, etc. These parameters can be obtained through experiments or manufacturer's technical documents, reflecting the external conditions of system operation. Each parameter is obtained through theoretical analysis and experimental verification in the initial stage of design. For example, the pipeline depth is designed according to the parallelism of the workload, and the cooling system efficiency is set according to the coolant type and flow rate.

[0076] b. Logic of performance estimation: In microarchitecture design, the performance estimation formula is used to predict the overall performance of the system. The formula is as follows: ω i and v j : These weight coefficients reflect the impact of microarchitecture parameters and environmental parameters on performance, which can be determined through experimental data or historical experience. For example, the impact of execution unit configuration on performance can be estimated through simulation data, while the impact of cooling system efficiency on power consumption and performance can be determined through cooling efficiency testing.

[0077] x i and e j :These are the specific parameter values ​​of the microarchitecture and the environment, corresponding to the design of the processor and the external environmental conditions. The formula weights the contribution of each parameter proportionally to obtain an overall performance estimate. Compared with the existing simple weighted average method, the formula of the present invention comprehensively considers the interaction between the internal parameters of the microarchitecture and the external environmental factors, especially under low-temperature superconducting conditions, the impact of the cooling system on performance cannot be ignored.

[0078] c. Performance error correction: After calculating the preliminary performance estimate, it may differ from the target performance P. target There is a certain error. To this end, the present invention proposes a performance error correction step: ΔP = P target -P estimate By calculating the gap between the actual estimated value and the target performance, a performance error can be obtained. This error reflects the reason why the system cannot achieve the target performance under the current microarchitecture parameters and environmental conditions.

[0079] d. Parameter correction: In order to eliminate performance errors, the algorithm proposes a parameter correction formula: Δx i =α·ΔP, α: is the correction coefficient, which can be tuned through multiple experiments or simulation tests. It is used to control the amplitude of each adjustment to ensure that fine-tuning does not cause major system instability. Δx i : This is the amount of microarchitecture parameter adjustment. The corresponding parameters are adjusted according to the size of the performance error. The core idea of ​​this formula is to reduce the performance error by gradually adjusting the design parameters of the microarchitecture. Compared with the existing static adjustment method, this feedback control mechanism can better adapt to diverse task requirements and environmental changes.

[0080] e. Update micro-architecture parameters: The micro-architecture parameters X′ = {x1′, x′2, ..., x′ n}, will become the input for the next round of optimization. This step gradually approaches the target performance through iterative optimization. Through multiple iterations, the system can dynamically adjust and optimize each microarchitecture parameter to adapt to complex operating environments. Compared with one-time optimization, this method can significantly improve the adaptability and robustness of the system.

[0081] The refined performance optimization algorithm in the present invention further refines the results of micro-architecture parameter calibration, aiming to make more precise adjustments to the calibrated micro-architecture parameters and take into account the impact of external environmental conditions on performance. This algorithm corrects errors through an error propagation model, so that the final micro-architecture parameters can achieve the best optimization effect under different operating conditions.

[0082] a. Receiving calibration parameters and error evaluation results: First, the algorithm receives the calibration parameters X′={x1′,x′2,...,x′} output by the microarchitecture preliminary parameter calibration algorithm. n} and error evaluation results. These calibration parameters are obtained based on preliminary performance estimation and error correction. These parameters are directly derived from the previous microarchitecture preliminary parameter calibration process, and have undergone a preliminary balance of basic performance, power consumption and area. The error evaluation results are calculated based on the gap between the actual system performance and the target performance. These parameters are the input for system optimization and are a combination of parameters after preliminary calibration, which can already reflect the basic performance requirements of the system.

[0083] b. Error correction model and correction function: According to the error propagation model, the error is corrected, and the correction function f(Δx i ,o i ) is used to correct the parameters: f(Δx i ,o i )=γ·Δx i +δ·h(o i ), Δx i is the parameter correction from the preliminary calibration step, representing the adjustment of the microarchitectural parameters; o i is the set of external factors O = {o1, o2, ..., o n}, including the efficiency of the cooling system, ambient temperature, etc. These external conditions can be monitored by sensors or calculated through the physical model of the cooling system; γ is the error adjustment coefficient, which is used to adjust the amplitude of the error correction and is usually set through experiments and simulations; δ is the external environment correction coefficient, which is used to adjust the impact of external conditions on microarchitecture parameters; h(o i ) is a nonlinear function related to external conditions, reflecting the impact of external conditions on system performance. The core idea of ​​this correction function is to combine the error correction value Δx of the internal microarchitecture parameters. i and external environmental factors i, further optimize the parameters. Compared with simple linear correction, this formula makes parameter optimization more accurate by considering the nonlinear influence of the external environment, especially maintaining the stability of system performance under different environmental conditions.

[0084] γ and δ are obtained through multiple simulations or experimental data tuning, which can ensure error correction adaptation under different conditions; external conditions o i It is provided by the actual operating environment and obtained in real time through the cooling system and environmental monitoring device; the microarchitecture parameters are updated according to the corrected error propagation results: the corrected parameter set X″={x1″,x′2′,...,x′ n ′}, the formula is as follows: i ″=x i ′+f(Δx i ,o i ), each parameter x i ″ is based on the initial calibration parameter x i ′ and correction function f(Δx i ,o i ). This formula generates a more accurate micro-architecture parameter combination by further modifying the preliminary parameters, ensuring that the system can still achieve optimal performance under different operating conditions. The correction function f(Δx i ,o i ) introduces external conditions o i , such as the performance of the cooling system and the ambient temperature. The traditional micro-architecture parameter adjustment method usually only focuses on the internal parameters of the processor, ignoring the influence of external factors such as the cooling system. The present invention significantly improves the accuracy of parameter adjustment by considering these external conditions; the correction function h(o i ) is a nonlinear function that can reflect the complex relationship between external conditions and system performance. This is more flexible than the traditional linear correction method and can more accurately capture the impact of changes in external factors on the system; by further correcting the preliminary calibration parameters, the present invention can ensure efficient operation of the system under different load and environmental conditions. Compared with a one-time calibration, the present invention enables continuous adjustment of micro-architecture parameters through iterative optimization to maintain the optimal state.

[0085] The comprehensive performance evaluation and decision algorithm is used to comprehensively analyze the calibrated microarchitecture parameters and accurate performance prediction values ​​to obtain the final performance evaluation results of the system. The algorithm combines the preliminary estimated performance and accurate performance prediction values, uses nonlinear combination functions for calculation, and dynamically adjusts the system parameter weights based on the results.

[0086] The formula is as follows: X′: is the micro-architecture parameter set obtained through preliminary calibration; X″: is the final micro-architecture parameter set after refined performance optimization; P e ' stimate :: Preliminary estimated performance value, based on microarchitecture calibration parameters X′. It predicts the performance of the processor under the current configuration through simulation, measurement or estimation model; P accurate : An accurate performance prediction value, which is obtained through more in-depth simulation or actual performance testing, and represents the actual performance of the system during operation; β1 and β2: are dynamically adjusted weight coefficients, which are adaptively adjusted according to the actual state of the system (such as load, power consumption requirements, etc.) to balance the impact of preliminary estimated performance and precise performance; in some cases, the system may need to increase the response speed. At this time, the weight of β1 will be increased, and more reliance will be placed on preliminary performance estimates to speed up the response.

[0087] In other scenarios, if more emphasis is placed on accurate performance (e.g., when the task is power-sensitive), the weight of β2 will be increased, and decisions will be made more dependent on accurate performance predictions;

[0088] Square root function processing preliminary performance estimate P e ' stimate , by using the square root, the impact of the initial estimate that may be too high on the overall assessment can be smoothed out, ensuring that there is no over-reliance on the estimate when the estimate is inaccurate or has large deviations; β2·log(1+P accurate ): Logarithmic function is used to process the accurate performance prediction value P accurate The logarithmic function can effectively suppress the impact of extreme values, ensuring that overestimation or underestimation of performance in extreme cases will not lead to deviations in the overall evaluation results.

[0089] Through this nonlinear combination function, a comprehensive performance index g(X′,X″,P accurate ), which is used for further microarchitecture configuration and decision optimization. The system can dynamically adjust microarchitecture parameters based on this performance indicator to achieve the best balance between performance and power consumption.

[0090] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for constructing a superconducting processor microarchitecture based on RISC-V, characterized in that: The following steps are involved: S1. Micro-architecture design: Based on the RISC-V instruction set architecture, design the functional modules and pipelines of the processor, and preset preliminary parameters to provide input basis for subsequent calibration and optimization; S2, parameter selection and simulation optimization, select and optimize microarchitecture parameters through simulation tools and optimization algorithms to ensure the balance of performance, power consumption and area; S3. Integration of low-temperature cooling system: design and integrate cooling system adapted to superconducting environment to ensure stable operation of processor under ultra-low temperature conditions; S4, Functional verification and performance testing, verifying the correctness of processor functions through simulation and actual testing, evaluating performance and optimizing; S5, Manufacturing and Packaging, using superconducting materials to manufacture key components and integrating the processor and cooling system into a package.

2. The method for constructing a superconducting processor microarchitecture based on RISC-V according to claim 1, characterized in that: The microarchitecture design includes the following steps: a. Based on the RISC-V instruction set architecture, design the functional modules of the processor, which include instruction pipeline, execution unit, register file, memory management unit and input / output interface; b. Expand the RISC-V instruction set, add new instructions for superconducting processors, including quantum bit initialization instructions, quantum gate operation instructions, and superconducting state detection instructions, and adjust the instruction decoding logic to make the new instructions compatible with the existing instruction set; c. Design at least three pipeline stages and integrate out-of-order execution and instruction-level parallel execution mechanisms in each pipeline stage; d. Preset microarchitecture parameters to provide input basis for the microarchitecture preliminary parameter calibration algorithm in subsequent steps.

3. The method for constructing a superconducting processor microarchitecture based on RISC-V according to claim 2, characterized in that: The parameter selection and simulation optimization include the following steps: a. According to the characteristics of the low-temperature superconducting environment, determine the number of execution units, cache levels and capacity, and the size of the register group, and limit the specific range of each parameter to adapt to the balance requirements of performance, power consumption, and area; b. Use simulation analysis tools to perform performance simulation on the selected microarchitecture parameters. The simulation results include the number of instructions executed per second, power consumption, and chip area. c. Use a multi-objective optimization algorithm to adjust the microarchitecture parameter combination based on the simulation results to achieve a balance between performance, power consumption and chip area; d. Apply the microarchitecture preliminary parameter calibration algorithm to calibrate the preliminarily set parameters, use the refined performance optimization algorithm to further optimize, and determine the final optimized configuration through comprehensive performance evaluation and decision-making algorithms.

4. The method for constructing a superconducting processor microarchitecture based on RISC-V according to claim 3, characterized in that: The integration of the cryogenic cooling system comprises the following steps: a. Design a cryogenic cooling system for a superconducting processor, the cooling system should be able to maintain the operating temperature of the processor between 2 Kelvin and 4 Kelvin; b. The cooling system is integrated into the packaging structure of the processor and is closely connected to the core structure of the processor, and the total length of the cooling path does not exceed 10 mm; c. The cooling system uses liquid helium or dilution refrigeration technology.

5. The method for constructing a superconducting processor microarchitecture based on RISC-V according to claim 4, characterized in that: The functional verification and performance testing includes the following steps: a. Perform functional verification on the simulation platform for different workloads to ensure that all instructions can be executed correctly; b. Test the number of instructions executed per second, average energy consumption and delay time performance indicators, and conduct statistical analysis on the test results; c. Based on the results of performance testing, identify performance limiting factors through bottleneck analysis and introduce optimization measures in the microarchitecture.

6. The method for constructing a superconducting processor microarchitecture based on RISC-V according to claim 5, characterized in that: The manufacturing and packaging comprises the following steps: a. Using superconducting materials to manufacture key components of the processor, the thickness of the material ranges from 5 nanometers to 100 nanometers; b. Make superconducting Josephson junctions with a size not exceeding 500 nanometers to ensure that the logic circuits of the processor have superconducting properties; c. The processor chip is packaged together with the cryogenic cooling system, and the overall size after packaging does not exceed 50 mm × 50 mm × 10 mm.

7. The method for constructing a superconducting processor micro-architecture based on RISCv according to claim 6, characterized in that: The microarchitecture preliminary parameter calibration algorithm includes the following steps: a. Collect the initial micro-architecture parameter data X = {x1, x2, ..., x n } and environmental parameters E={e1,e2,...,e m }, the microarchitecture parameters include execution unit configuration, pipeline depth and cache size, and the environmental parameters include cooling system efficiency and temperature; b. Calculate the preliminary performance estimate P estimate , where ω i and e j is the weight coefficient, reflecting the influence of each parameter on the performance; c. According to the performance error ΔP = P target -P estimate , perform preliminary calibration on the microarchitecture parameters, the correction amount is: Δx i =α·ΔP, where α is the calibration coefficient; d. Update the microarchitecture parameters to obtain the calibrated parameters X′={x1′,x′2,...,x′ n }.

8. The method for constructing a superconducting processor micro-architecture based on RISCv according to claim 7, characterized in that: The refined performance optimization algorithm includes the following steps: a. Receive the calibration parameters X′ and error evaluation results output by the microarchitecture preliminary parameter calibration algorithm, as well as the external conditions O = {o1, o2, ..., o n }, the external conditions include cooling system performance and ambient temperature; b. Based on the error propagation model, the error is corrected. The correction function f is defined as: f(Δx i ,o i )=γ·Δx i +δ·h(o i ), where γ is the error adjustment coefficient, h(o i ) is a nonlinear function related to external conditions; c. Update the microarchitecture parameters based on the corrected error propagation results: x i ″=x i ′+f(Δx i ,o i ), Get the modified parameter set X″={x1″,x′2′,...,x′ n ′}.

9. The method for constructing a superconducting processor micro-architecture based on RISCv according to claim 8, characterized in that: The comprehensive performance evaluation and decision-making algorithm includes the following steps: a. Receive the output results of the preliminary microarchitecture parameter calibration and refined performance optimization, including the calibrated parameters X′, optimized parameters X″ and accurate performance prediction P accurate ; b. Use the nonlinear combination function g to evaluate the comprehensive performance of the above results. The nonlinear combination function is defined as: Among them, β1 and β2 are dynamic weights, which are adaptively adjusted according to different conditions; c. Apply dynamic weight adjustment mechanism based on comprehensive performance evaluation results; d. Output the final comprehensive performance index S and the optimized microarchitecture configuration.

Images